Data Engineering & Architecture
- Design, develop, and maintain scalable, high-performance data pipelines
- Work extensively with Azure Data Factory and Microsoft Fabric
- Build robust ETL/ELT frameworks using Python
- Design and optimize Lakehouse / Data Warehouse architectures
- Handle large-scale datasets efficiently (high volume and throughput)
- Write and optimize complex SQL queries for performance and reliability
- Integrate data from multiple sources including APIs, transactional systems, and external platforms

Leadership & Delivery (Hands-on)
- Lead and mentor a team of data engineers while remaining actively involved in coding and solution design
- Perform hands-on development for critical pipelines, complex transformations, and performance optimisation.
- Conduct code reviews and enforce best practices, design patterns, and coding standards
- Act as the technical owner for data engineering deliverables

Quality, Performance & Reliability
- Implement data quality checks, validations, and monitoring
- Optimize pipelines for performance, scalability, and cost




- Ensure reliability, fault tolerance, and error handling in production systems
- Follow data security, access control, and compliance best practices
- Lead troubleshooting, root-cause analysis, and production issue resolution

Collaboration & Continuous Improvement
- Work closely with BI, analytics, product, and business teams
- Translate business requirements into scalable technical solutions
- Stay up to date with up-to-date data engineering tools, technologies, and techniques
- Proactively suggest architectural and process improvement

Requirements
- 3-6 years of experience in the Data Engineering field.
- Strong hands-on experience in Python for data engineering, including building and maintaining production-grade, large-scale data pipelines
- Advanced experience with Azure Data Factory and Azure-based data platforms for orchestration, integration, and scalable data processing
- Working experience wit

📌 Data Engineer (Noida)
🏢 Scaleupally
📍 Noida